Athanas Argus, McCorrison Jamison, Campistron Julie, Bender Nick, Price Jamie, Smalley Susan, Schork Nicholas J
Bioinformatics and Systems Biology, University California San Diego, San Diego, CA, United States.
Stop, Breathe & Think, Inc, Los Angeles, CA, United States.
JMIR Ment Health. 2021 Mar 2;8(3):e19832. doi: 10.2196/19832.
The increasing demand for mental health care, a lack of mental health care providers, and unequal access to mental health care services have created a need for innovative approaches to mental health care. Digital device apps, including digital therapeutics, that provide recommendations and feedback for dealing with stress, depression, and other mental health issues can be used to adjust mood and ultimately show promise to help meet this demand. In addition, the recommendations delivered through such apps can also be tailored to an individual's needs (ie, personalized) and thereby potentially provide greater benefits than traditional "one-size-fits-all" recommendations.
This study aims to characterize individual transitions from one emotional state to another during the prolonged use of a digital app designed to provide a user with guided meditations based on their initial, potentially negative, emotional state. Understanding the factors that mediate such transitions can lead to improved recommendations for specific mindfulness and meditation interventions or activities (MMAs) provided in mental health apps.
We analyzed data collected during the use of the Stop, Breathe & Think (SBT) mindfulness app. The SBT app prompts users to input their emotional state before and immediately after engaging with MMAs recommended by the app. Data were collected from more than 650,000 SBT users engaging in nearly 5 million MMAs. We limited the scope of our analysis to users with 10 or more MMA sessions that included at least 6 basal emotional state evaluations. Using clustering techniques, we grouped emotions recorded by individual users and then applied longitudinal mixed effect models to assess the associations between individual recommended MMAs and transitions from one group of emotions to another.
We found that basal emotional states have a strong influence on transitions from one emotional state to another after MMA engagement. We also found that different MMAs impact these transitions, and many were effective in eliciting a healthy transition but only under certain conditions. In addition, we observed gender and age effects on these transitions.
We found that the initial emotional state of an SBT app user determines the type of SBT MMAs that will have a favorable effect on their transition from one emotional state to another. Our results have implications for the design and use of guided mental health recommendations for digital device apps.
对心理健康护理的需求不断增加、心理健康护理提供者短缺以及获得心理健康护理服务的机会不平等，都促使人们需要创新的心理健康护理方法。包括数字疗法在内的数字设备应用程序，可为应对压力、抑郁和其他心理健康问题提供建议和反馈，可用于调节情绪，并最终有望帮助满足这一需求。此外，通过此类应用程序提供的建议还可根据个人需求进行定制（即个性化），从而可能比传统的“一刀切”建议带来更大的益处。
本研究旨在描述在长时间使用一款数字应用程序期间，个体从一种情绪状态转变为另一种情绪状态的情况。该应用程序旨在根据用户最初可能消极的情绪状态为其提供引导式冥想。了解介导此类转变的因素可改进针对心理健康应用程序中特定正念和冥想干预或活动（MMAs）的建议。
我们分析了在使用“停止、呼吸与思考”（SBT）正念应用程序期间收集的数据。SBT应用程序会提示用户在参与该应用程序推荐的MMAs之前和之后立即输入他们的情绪状态。数据收集自65万多名参与近500万次MMAs的SBT用户。我们将分析范围限制在进行了10次或更多次MMA会话且至少进行了6次基础情绪状态评估的用户。使用聚类技术，我们对个体用户记录的情绪进行分组，然后应用纵向混合效应模型来评估个体推荐的MMAs与从一组情绪转变为另一组情绪之间的关联。
我们发现基础情绪状态对参与MMA后从一种情绪状态转变为另一种情绪状态有很大影响。我们还发现不同的MMAs会影响这些转变，许多MMAs在引发健康转变方面是有效的，但仅在某些条件下。此外，我们观察到性别和年龄对这些转变有影响。
我们发现SBT应用程序用户的初始情绪状态决定了哪种SBT MMAs将对他们从一种情绪状态转变为另一种情绪状态产生有利影响。我们的结果对数字设备应用程序的引导式心理健康建议的设计和使用具有启示意义。
